MCP Catalogs
Home

mcp-server-chart vs datagouv-mcp

Side-by-side comparison to help you pick between these two MCP servers.

mcp-server-chart
by antvis
datagouv-mcp
by datagouv
Stars★ 4,068★ 1,460
30d uses10,239
Score8455
Official
Categories
AI / LLM ToolsDeveloper ToolsProductivity
AI / LLM ToolsDatabaseSearch
LanguageTypeScriptPython
Last committhis monththis month

mcp-server-chart · Summary

A TypeScript MCP server for generating 26+ visualization charts using AntV, supporting multiple chart types and deployment options.

datagouv-mcp · Summary

Official MCP server for data.gouv.fr that enables AI chatbots to search and analyze French open data.

mcp-server-chart · Use cases

  • Data analysts creating visual reports from datasets
  • AI assistants generating custom charts based on user requests
  • Web applications embedding visualization capabilities via HTTP API

datagouv-mcp · Use cases

  • Ask about real estate prices in specific French regions
  • Retrieve latest demographic data for French cities
  • Search and analyze public datasets through conversational AI

mcp-server-chart · Install

Installation

Install globally:

npm install -g @antv/mcp-server-chart

For Desktop Apps (e.g., Claude Desktop, VSCode):

{
  "mcpServers": {
    "mcp-server-chart": {
      "command": "npx",
      "args": ["-y", "@antv/mcp-server-chart"]
    }
  }
}

For Windows:

{
  "mcpServers": {
    "mcp-server-chart": {
      "command": "cmd",
      "args": ["/c", "npx", "-y", "@antv/mcp-server-chart"]
    }
  }
}

datagouv-mcp · Install

Installation

Using Public Hosted Server

The recommended approach is to use the public instance at https://mcp.data.gouv.fr/mcp.

Claude Desktop Configuration

Add to your Claude Desktop configuration file:

{
  "mcpServers": {
    "datagouv": {
      "command": "npx",
      "args": [
        "mcp-remote",
        "https://mcp.data.gouv.fr/mcp"
      ]
    }
  }
}

Local Installation with Docker

git clone git@github.com/datagouv/datagouv-mcp.git
cd datagouv-mcp
docker compose up -d

Manual Installation

# Install dependencies
uv sync

# Copy environment file
cp .env.example .env

# Start the server
uv run main.py
Comparison generated from public README + GitHub signals. Last updated automatically.